OpenOmics provides a bioinformatics API and web-app platform integrate and visualize the multiomics and clinical data.
Project description
This Python package provide a series of tools to integrate and query the genomics, transcriptomics, proteomics, and clinical data (aka multi-omics data). With scalable data-frame manipulation tools, OpenOmics facilitates the common data wrangling tasks when preparing data for RNA-seq bioinformatics analysis.
Documentation (Latest | Stable) | OpenOmics at a glance
Features
OpenOmics assist in integration of heterogeneous multi-omics bioinformatics data. The library provides a Python API as well as an interactive Dash web interface. It features support for:
- Genomics, Transcriptomics, Proteomics, and Clinical data.
- Harmonization with 20+ popular annotation, interaction, disease-association databases.
OpenOmics also has an efficient data pipeline that bridges the popular data manipulation Pandas library and Dask distributed processing to address the following use cases:
- Providing a standard pipeline for dataset indexing, table joining and querying, which are transparent and customizable for end-users.
- Providing Efficient disk storage for large multi-omics dataset with Parquet data structures.
- Integrating various data types including interactions and sequence data, then exporting to NetworkX graphs or data generators for down-stream machine learning.
- Accessible by both developers and scientists with a Python API that works seamlessly with an external Galaxy tool interface or the built-in Dash web interface (WIP).
Installation via pip:
$ pip install openomics
Citations
The journal paper for this scientific package is currently being reviewed. In the meanwhile, the current package version can be cited with:
# BibTeX
@software{nhat_jonny_tran_2021_4552831,
author = {Nhat Tran and
Jean Gao},
title = {{BioMeCIS-Lab/OpenOmics: Bug fixes from pyOpenSci
Reviewer 2}},
month = feb,
year = 2021,
publisher = {Zenodo},
version = {v0.8.5},
doi = {10.5281/zenodo.4552831},
url = {https://doi.org/10.5281/zenodo.4552831}
}
Credits
This package was created with Cookiecutter and the pyOpenSci/cookiecutter-pyopensci project template, based off audreyr/cookiecutter-pypackage.
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